Wi-Fi location relies on a simple physical principle: any device connected to a wireless network continuously exchanges radio signals with nearby access points. By analyzing these signals, their strength, and their propagation time, an algorithm can estimate the position of a terminal, and by extension, that of the person carrying it. This technique works where GPS fails, particularly inside buildings.
Radio Principle Behind Wi-Fi Geolocation
Each router or Wi-Fi access point emits a unique identifier called a MAC address (Media Access Control). Devices within range capture these identifiers and measure the strength of the received signal, expressed in dBm. The closer a device is to the access point, the stronger the signal.
Location relies on a comparison between the captured signals and a global database that associates each MAC address with geographical coordinates. Google, Apple, and other players feed these databases by collecting information from Wi-Fi access points detected by smartphones during their travels.
When an Android phone or another device scans nearby Wi-Fi networks, it sends the list of detected access points to a server. The server cross-references this data with its mapping and returns a position estimate. Understanding this Wi-Fi location method helps explain why accuracy varies significantly depending on the environment.
In dense urban areas, where Wi-Fi access points are numerous, accuracy can reach a few meters. In rural areas, with few referenced access points, the estimation remains approximate.
Trilateration and Fingerprinting: Two Indoor Positioning Techniques
Two approaches dominate indoor Wi-Fi location. They do not work the same way and do not offer the same accuracy.
Signal Strength Trilateration
Wi-Fi trilateration uses at least three access points with known positions. The device measures the strength of the signal received from each, converts this strength into an estimated distance, and then calculates its position at the intersection of the three theoretical circles. The result directly depends on the quality of the strength-distance conversion, which is disrupted by walls, furniture, and signal reflections.
Radio Fingerprinting
Fingerprinting works differently. A calibration phase involves recording, at many points in a building, the perceived radio signature (which networks, at what strength). These readings form a reference map. When a device locates itself, it compares its current radio signature with the map and identifies the most likely area.
Fingerprinting offers better accuracy in complex environments (shopping malls, hospitals, airports), but it requires prior mapping work that can become outdated as soon as a wall is moved or an access point is added.
IEEE 802.11bf Standard and Device-Free Presence Detection
Wi-Fi location has long assumed that the person being sought carries a smartphone or connected device. Since September 2025, the IEEE 802.11bf-2025 standard formalizes a different use of Wi-Fi: presence, distance, and motion detection by analyzing disturbances in the radio signal within a room.
The principle is based on the fact that a human body absorbs and reflects Wi-Fi waves. A compatible router can analyze variations in its own signal to determine if a person is in the room, at what approximate distance, and if they are moving. This capability, called “Wi-Fi sensing,” requires no additional sensors.
In October 2025, a team from the Karlsruhe Institute of Technology (KIT) presented a system named BFId (Beamforming Feedback Identification) at the ACM CCS 2025 conference. This system identifies a person among a group based solely on the disturbances they cause to Wi-Fi signals, without a camera and without the person carrying a smartphone. The reported accuracy reaches 99.5% on a sample of 197 subjects.
Concrete Applications and Limitations of Wi-Fi Location
The most widespread use remains indoor geolocation on smartphones. Indoor navigation applications (in train stations, hospitals, or shopping malls) combine Wi-Fi data with other sensors to guide the user. Google uses Wi-Fi location as a complement to GPS on Android, particularly to speed up the initial position fix or to maintain location when the satellite signal is lost.
Wi-Fi sensing opens up other perspectives:
- Presence detection in a smart home to trigger lighting or heating without a dedicated motion sensor
- Monitoring elderly people living alone by detecting a prolonged absence of movement without resorting to a camera
- Home security, as proposed by Comcast with its Xfinity Shield platform launched in August 2026, which turns routers into motion detectors
These uses raise privacy concerns. Wi-Fi sensing works without the active consent of the detected person, as they do not need to carry a device or be connected to the network. The 802.11bf standard does not provide a mechanism for passive user opt-out.
In terms of accuracy, Wi-Fi location remains inferior to BLE (Bluetooth Low Energy) for meter-level positioning indoors. Wi-Fi offers broader coverage but less fine spatial resolution. To locate a person within a building, combining both technologies yields the best results.
Reliability also depends on the density of the Wi-Fi network. An apartment with a single router will only allow for binary presence detection (in the room or not). An open space equipped with dozens of access points will allow for much more granular tracking.
Wi-Fi does not replace GPS outdoors, but it fills a blind spot that the satellite signal does not cover. With the standardization of Wi-Fi sensing and its gradual integration into consumer routers, the boundary between communication network and location sensor is fading.
